The Future of GPT4All
In the future, we will continue to grow GPT4All, supporting it as the de facto solution for LLM accessibility.
Table of Links
2.1 Data Collection and Curation
2.2 Model Training, 2.3 Model Access and 2.4 Model Evaluation
3 From a Model to an Ecosystem
3.1 GPT4All-J: Repository Growth and the implications of the LLaMA License
3.2 GPT4All-Snoozy: the Emergence of the GPT4All Ecosystem
3.3 The Current State of GPT4All
4 The Future of GPT4All
In the future, we will continue to grow GPT4All, supporting it as the de facto solution for LLM accessibility. Concretely, this means continuing to compress and distribute important open-source language models developed by the community, as well as compressing and distributing increasingly multimodal AI models. Furthermore, we will expand the set of hardware devices that GPT4All models run on, so that GPT4All models “just work" on any machine, whether it comes equipped with Apple Metal silicon, NVIDIA, AMD, or other edgeaccelerated hardware. Overall, we envision a world where anyone, anywhere, with any machine, can access and contribute to the cutting edge of AI.
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:::info This paper is available on arxiv under CC BY 4.0 DEED license.
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:::info Authors:
(1) Yuvanesh Anand, Nomic AI, yuvanesh@nomic.ai;
(2) Zach Nussbaum, Nomic AI, zach@nomic.ai;
(3) Adam Treat, Nomic AI, adam@nomic.ai;
(4) Aaron Miller, Nomic AI, aaron@nomic.ai;
(5) Richard Guo, Nomic AI, richard@nomic.ai;
(6) Ben Schmidt, Nomic AI, ben@nomic.ai;
(7) GPT4All Community, Planet Earth;
(8) Brandon Duderstadt, Nomic AI, brandon@nomic.ai with Shared Senior Authorship;
(9) Andriy Mulyar, Nomic AI, andriy@nomic.ai with Shared Senior Authorship.
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